Race, Technology, and Trust: Examining the Cheating Discourse Among Black and Asian AI Users

Artificial Intelligence (AI) is emerging in academia and presents innovative and idealistic opportunities for many students. As with any new technological craze, there is the challenge of biased humanistic influence, which can sometimes cause apprehension in technological use. This study examines the existing notions of cultural biases and presumptions of cheating by Black and Asian (AI) users. We evaluate the implication that Black and Asian students may be less than honest in academia, specifically when using AI tools. Studies show that marginalized students are sometimes affected by systematic racial constructs, deeming them less than truthful when using technology to assist in educational activities. Critical technocultural discourse analysis (CTDA) and autoethnography, a research method involving the researchers' personal experiences and reflections, will examine Black and Asian students' cheating discourse. CTDA is a multimodal method that assesses digital social phenomena from cultural theorists, feminist, and technological perspectives to examine technocultural findings. Moreover, CTDA formulates technology as a societal representation of social constructs and investigates technological associations of digital phenomena. We evaluate recent studies to share contextual commonalities and thematic experiences of Black and Asian AI users, highlighting marginalized narratives and demonstrating our findings.